BI Business Intelligence & Data Analytics Training in Bangalore

BI Business Intelligence and Data Analytics Training in Bangalore is provided at Upshot Technologies. We offer a valuable business intelligence certification course. Our data analytics training bangalore is offered by expert trainers in the industry.

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Benefits of learning business intelligence and analytics From Upshot

Be it professional development or upskilling, learning relevant and in-demand skills can help you become a competitive and valuable employee with important skills. With that said, here we bring to you highly-rewarding BI Business Intelligence and Data Analytics Training in Bangalore. We are the top Business Intelligence training institute in Bangalore. Joining here can benefit you with:

  • Hours of Online Live Instructor-led Classes
  •  Project Work to provide hands-on knowledge
  •  Best Course Completion Rate in industry
  •  Training by industry experts
  •  Self-paced tutorials on business intelligence and data analytics.

About business intelligence and analytics courses in Bangalore

 

Business intelligence and analytics courses in Bangalore help businesses analyse and structure their highly unstructured data. This helps to improve their efficiency, scalability and reduced costs. What will you learn in this course? 

 

  • Get expertise with analytics, Tableau, and SQL
  • Build problem-solving skills in business 
  • Gather, organize and evaluate and visualize data Using data with an improved business decision making 
  • Provide data information in reports, KPIs, and dashboards 
  • Learn to Perform qualitative as well as quantitative business analysis Analyze the unstructured data
  • Learn mastering business intelligence course online
  • Get data analytics certification courses
  • Create databases and dashboards making use of Tableau, Qlikview, Qlik Sense, etc.

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FAQ Frequently Asked Questions

Is the certification course for Business intelligence worth it?

If you think about the value for your career, then it is absolutely yes. 

Is the certification course for Business intelligence worth it?

If you think about the value for your career, then it is absolutely yes. 

Is the certification course for Business intelligence worth it?

If you think about the value for your career, then it is absolutely yes. 

Is the certification course for Business intelligence worth it?

If you think about the value for your career, then it is absolutely yes. 

Is the certification course for Business intelligence worth it?

If you think about the value for your career, then it is absolutely yes. 

Is the certification course for Business intelligence worth it?

If you think about the value for your career, then it is absolutely yes. 

Is the certification course for Business intelligence worth it?

If you think about the value for your career, then it is absolutely yes. 

Course description:

Every data science project begins with importing data. In this business intelligence courses in Bangalore, you’ll learn the basics and beyond, starting with how data is structured. Learn how to import data from the most common formats and external sources.

Faculty: 

  • Expert instructor available at your convenient time*.
  • They conduct Workshops and assessments
  • Real Life Project Case Studies
  • They give you guidance accordingly
  • Extensive professional experience 
  • They have worked with the top global companies.

Curriculum: 

  • Valuable insights into Business intelligence
  • Latest tools, techniques, and skills a BI professional must know
  • Insights on how to advance your career in business intelligence
  • Discussion of the hottest career options available
  • Detailed information on BI certification on technology professionals
  • Data analytics certification courses.

Job Outcomes: 

  • Owing to its diverse set of applications, BI has emerged as one of the most in-demand career paths for young professionals
  • Upskilling in Business intelligence and data analytics will certainly set you in the path of a high-flying career.

Module 1

  • Big Data Introduction and Hadoop
  • → Fundamental
  • → Data Storage & Analysis
  • → Comparision with RDBMS
  • → HDFS ARCHITECTURE
  • → Basic Terminologies
  • → HDFS Block Concepts
  • → Replication Concepts
  • → Basic reading & writing of files in HDFS
  • → Basic processing concepts in MapReduce
  • → Data Flow
  • → Anatomy of file READ and WRITE

Module 4

  • DATA PROCESSING
  • MapReduce:
  • Env Setup
  • Tool and ToolRunner
  • Mapper
  • Reducer
  • Driver program
  • How to package the job?
  • MapReduce WebUI
  • How MapReduce Job run?
  • Shuffle & Sort
  • Speculative Execution
  • InputFormats
  • Input Splits and Record Reader
  • Default Input Formats
  • Implement Custom Input Format
  • OutputFormats
  • Default Output formats
  • Output Record Reader
  • Compression
  • Map Output

Module 2

  • HADOOP ADMINISTRATOR
  • HADOOP GEN1 VS HADOOP GEN 2(YARN)
  • Linux commands
  • Single and Multinode cluster installation (HADOOP Gen 2)
  • AWS (EC2, RDS, S3, IAM and Cloud formation)
  • Cloudera and Hortonworks distribution installation on AWS
  • Cloudera Manager and Ambari
  • Hadoop Security and Commissioning and Decommissioning of nodes
  • Sizing of Hadoop Cluster and Name Node High Availability

Module 5

  • An Introduction to Python
  • 1.1 Brief about the course
  • 1.2 History/timelines of Python
  • 1.3 What is python ?
  • 1.4 What python can do?
  • 1.5 How the name was put up as python
  • 1.6 Why python?
  • 1.7 Who all are using python
  • 1.8 Features of python
  • 1.9 Python installation
  • 1.10. Hello world
  • 1. using cmd
  • 2. IDLE
  • 3. By py script
  • 4. python command line
  • 2: Beginning Python Basics
  • 2.1. The print statements
  • 2.2. Comments
  • 2.3. Python Data Structures
  • 2.4. variables & Data Types
  • 1. rules for variable
  • 2. declaring variables
  • 3. Assignment in variables
  • 4. operations with variables
  • 5. Reserved keyword
  • 2.5. Operators in Python
  • 2.6. Simple Input & Output
  • 2.7. Examples for variables , Data Types ,operators
  • 3: Python Program Flow
  • 3.1. Indentation
  • 3.2. The If statement and its' related statement
  • 3.3. An example with if and it's related statement
  • 3.4. The while loop
  • 3.5. The for loop
  • 3.6. The range statement
  • 3.7. Break
  • 3.8. Continue
  • 3.9. pass
  • 3.9. Examples for looping
  • 4: Functions & Modules
  • 4.1. system define function(number system and its sdf ,String and its sdf
  • )
  • 4.2. Create your own functions (user define function)
  • 4.3. Functions Parameters
  • 4.4. Variable Arguments
  • 4.5. An Exercise with functions
  • 5: Exceptions
  • 5.1. Errors
  • 5.2. Exception Handling with try
  • 5.3. Handling Multiple Exceptions
  • 5.4. raise
  • 5.5. finally
  • 5.6. else
  • 6: File Handling
  • 6.1. File Handling Modes
  • 6.2. Reading Files
  • 6.3. Writing & Appending to Files
  • 6.4. Handling File Exceptions
  • 7: Data Structures and Data Structures functions
  • 7.1. List and its sdf
  • 7.2. tuple and its sdf
  • 7.3. Dictionary and its sdf
  • 7.4. set and its sdf
  • 7.5. use cases and practical examples
  • 8: casting
  • 8:1 intro to casting

Module 3

  • DATA INGESTION
  • Sqoop:
  • Migration of data from MYSQL/ ORACLE to HDFS.
  • Creating SQOOP job.
  • Scheduling and Monitoring SQOOP job using OOZIE and Crontab.
  • Incremental and Last modified mode in sqoop.
  • Talend:
  • Installation of Talend big data studio on windows server.
  • Creating and Scheduling talend Jobs.
  • Components: tmap, tmssqlinput, tmssqloutput,tFileInputDelimited, tfileoutputdelimited, tmssqloutputbulkexec, tunique, tFlowToIterate,tIterateToFlow, tlogcatcher, tflowmetercatcher, tfilelist, taggregate, tsort, thdfsinput, thdfsoutput, tFilterRow, thiveload.
  • Flume:
  • Flume Architecture
  • Data Ingest in HDFS with Flume
  • Flume Sources
  • Flume Sinks
  • Topology Design Considerations

Module 6

  • NOSQL
  • Cassandra:
  • Cassandra cluster installation
  • Cassandra Architecture
  • Cqlsh
  • Replication strategy
  • Tools: Opscenter, Nodetool and CCM
  • Cassandra use cases
  • Labs:
  • Real Time use cases and Data sets covered (10+ Real Time datasets)
  • Word count, Sensors (Weather Sensors) Dataset, Social Media data sets like YouTube, Twitter data analysis
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